FA-11226 / Media timeline seeking / Open access
Presentation time offset subtracted · case 01
Ignoring presentation-time offset misaligns a segment timeline.
ROOT CAUSE
Ignoring presentation-time offset misaligns a segment timeline.
VERIFIED REPAIR
Preserve the media contract: Convert integer media ticks to presentation seconds by subtracting the presentation offset in the same tick units before dividing by positive timescale.
Unsuccessful approach: Subtracting tick-valued offset from seconds mixes incompatible units.
Case contract
Convert integer media ticks to presentation seconds by subtracting the presentation offset in the same tick units before dividing by positive timescale.
Why this case matters
A deterministic local media controller stage; metadata and downloaded data are supplied explicitly. No external player, service or codec is required.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(ticks, timescale, offset_ticks):
return ticks/timescale
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*(1500, 1000, 500)),1)
check('fixture 2',solve(*(90000, 90000, 45000)),0.5)
check('fixture 3',solve(*(0, 1, 0)),0)
check('fixture 4',solve(*(250, 1000, 500)),-0.25)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| fixture 1 | 1.5 | 1 | Failed |
| fixture 2 | 1.0 | 0.5 | Failed |
| fixture 3 | 0.0 | 0 | Passed |
| fixture 4 | 0.25 | -0.25 | Failed |
SHA-256 / 316408e0d058a1a0d1a460981a6511f8e589fdd71f14c47adce923acaa088959
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(ticks, timescale, offset_ticks):
return ticks/timescale-offset_ticks
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*(1500, 1000, 500)),1)
check('fixture 2',solve(*(90000, 90000, 45000)),0.5)
check('fixture 3',solve(*(0, 1, 0)),0)
check('fixture 4',solve(*(250, 1000, 500)),-0.25)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| fixture 1 | -498.5 | 1 | Failed |
| fixture 2 | -44999.0 | 0.5 | Failed |
| fixture 3 | 0.0 | 0 | Passed |
| fixture 4 | -499.75 | -0.25 | Failed |
SHA-256 / 8c37f3478ad27fd24cb291f406af87b86983e784c9d88a3627c3f0683e84809e
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(ticks, timescale, offset_ticks):
return (ticks-offset_ticks)/timescale
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*(1500, 1000, 500)),1)
check('fixture 2',solve(*(90000, 90000, 45000)),0.5)
check('fixture 3',solve(*(0, 1, 0)),0)
check('fixture 4',solve(*(250, 1000, 500)),-0.25)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| fixture 1 | 1.0 | 1 | Passed |
| fixture 2 | 0.5 | 0.5 | Passed |
| fixture 3 | 0.0 | 0 | Passed |
| fixture 4 | -0.25 | -0.25 | Passed |
SHA-256 / 2e320d66d544377921eafe4a935df9c72e48de7c126c39c41f34768a3cb0e911
Verification & scope
This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.
Observations recorded using Python 3.12.14 at 2026-09-29T14:38:46.135222+00:00.
Case digest / a387bf32294e84475a572725d9306792cd204d3edbbe2a10d377ee09b31e911c